Sensitivity Analysis of the Agricultural Policy/Environmental eXtender (APEX) for Phosphorus Loads in Tile-Drained Landscapes

Ford, William I.; King, Kevin W.; Williams, Mark R.; Williams, J. R.; Fausey, Norman R.

doi:10.2134/jeq2014.12.0527

Cited by 22 publications

(21 citation statements)

References 42 publications

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“…Rapid vertical transit of water to tile drains can occur during both saturated and unsaturated field conditions. One possible macropore pathway is associated with rapid vertical flux through earthworm burrows, root channels, and inter‐aggregate voids when saturation exceeds the “water‐entry” pressure of micropores, herein referred to as matrix‐excess macropore (MEM) flow (Jarvis, 2007; Deurer et al, 2009; Beven and Germann, 2013). Macropore flow has also been observed to occur at low antecedent moisture conditions as a result of desiccation crack networks that create direct conduits to subsurface pathways and the groundwater table, herein referred to as matrix‐desiccation macropore (MDM) flow (Bouma et al, 1978; Kneale and White, 1984; Shipitalo and Gibbs, 2000; Nimmo, 2012; Mirus and Nimmo, 2013).…”

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confidence: 99%

Modified APEX model for Simulating Macropore Phosphorus Contributions to Tile Drains

Ford

King²,

Williams

et al. 2017

J of Env Quality

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The contribution of macropore flow to phosphorus (P) loadings in tile-drained agricultural landscapes remains poorly understood at the field scale, despite the recognized deleterious impacts of contaminant transport via macropore pathways. A new subroutine that couples existing matrix-excess and matrix-desiccation macropore flow theory and a modified P routine is implemented in the Agricultural Policy Environmental eXtender (APEX) model. The original and modified formulation were applied and evaluated for a case study in a poorly drained field in Western Ohio with 31 months of surface and subsurface monitoring data. Results highlighted that a macropore subroutine in APEX improved edge-of-field discharge calibration and validation for both tile and total discharge from satisfactory and good, respectively, to very good and improved dissolved reactive P load calibration and validation statistics for tile P loads from unsatisfactory to very good. Output from the calibrated macropore simulations suggested median annual matrix-desiccation macropore flow contributions of 48% and P load contributions of 43%, with the majority of loading occurring in winter and spring. While somewhat counterintuitive, the prominence of matrix-desiccation macropore flow during seasons with less cracking reflects the importance of coupled development of macropore pathways and adequate supply of the macropore flow source. The innovative features of the model allow for assessments of annual macropore P contributions to tile drainage and has the potential to inform P site assessment tools.

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confidence: 99%

Modified APEX model for Simulating Macropore Phosphorus Contributions to Tile Drains

Ford

King²,

Williams

et al. 2017

J of Env Quality

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“…Numerical models, such as the NTT, are often criticized because many of them do not adequately capture P losses in subsurface pathways (Radcliffe et al, 2015), which is an important concern for states like Ohio where leaching can pose a large risk for P loss. A recent study, using a subset of the field dataset reported herein, showed that the Agricultural Policy/Environmental eXtenter (APEX) model, which is utilized as part of the NTT, was able to accurately simulate surface and subsurface P loading at annual timescales (Ford et al, 2015). Given the performance of the current Ohio PI and numerical models to predict a field's risk of P loss in tile‐drained landscapes, future research efforts should focus on using field datasets to calibrate and validate multiple‐site assessment tools to determine an accurate and preferred P management tool for Ohio so that consistent and reliable recommendations are made.…”

Section: Discussionmentioning

confidence: 99%

Edge‐Of‐Field Evaluation of the Ohio Phosphorus Risk Index

et al. 2017

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The Phosphorus Index (PI) has been the cornerstone for phosphorus (P)-based management and planning over the past twenty years, yet field-scale evaluation of many state PIs has been limited. In this study, P loads measured in surface runoff and tile discharge from 40 agricultural fields in Ohio with prevailing management practices were used to evaluate the Ohio PI. Annual P loads were highly variable among fields (dissolved reactive P: 0.03-4.51 kg ha, total P: 0.03-6.88 kg ha). Both measured annual dissolved reactive P ( = 0.36, < 0.001) and total P ( = 0.25, < 0.001) loads were significantly related to Ohio PI score. The relationship between measured load and PI score substantially improved when averaged annual field values were used (dissolved reactive P: = 0.71, total P: = 0.73), indicating that the Ohio PI should be utilized to evaluate average annual risk of P loss, rather than as an annual risk tool. Comparison between the Ohio PI and other established local and national metrics resulted in large differences in potential P management recommendations for the monitored fields. In the near term, revision of Ohio PI risk categories and management recommendations using local P loading thresholds is needed. To meet the minimum criteria for state PI tools, future research efforts should focus on using measured field data (i) to incorporate new input factors (i.e., P application timing and leaching potential) into the Ohio PI, and (ii) to calibrate and validate the Ohio PI to provide better P risk assessments and management recommendations.

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“…The APEX can also be used to assess the impact of land management practices, conservation practices, and global climate change. Furthermore, the APEX has the ability to assess the sustainability of agricultural system on a whole farm for a long term (1-4000 years) [17,20].…”

Section: Apex Model Descriptionmentioning

confidence: 99%

Sensitivity Analysis of the APEX Model for Assessing Sustainability of Switchgrass Grown for Biofuel Production in Central Texas

Zhang

Juenger

Osorio³

et al. 2017

Bioenerg. Res.

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Crop simulation models are increasingly being used to understand the feasibility of large-scale cellulosic biofuel production along with the multi-dimensional impacts on environmental sustainability. However, how the uncertainty in model parameters impacts model performance for sustainability is unclear. In this case study, sensitivity analyses were conducted for three switchgrass sustainability metrics: total biomass production, nitrogen loss, and soil carbon change using the APEX (Agricultural Policy/Environmental eXtender) model. Fifteen out of the 45 parameters (25 crop growth (CROP) parameters and 20 additional model parameters (PARM)) were identified as influential for the three sustainability metrics for three lowland genotypes (WBC, AP13, and KAN) across two locations (Temple, TX, and Austin, TX). Our sensitivity results showed that parameter importance was not dependent on the genotypes but depended on the variables of interest, and differed only slightly between locations. Influential belowground-related CROP and PARM parameters were identified for each sustainability metric, indicating that belowground-related parameters are just as important as commonly measured aboveground CROP parameters.Further investigation of the linear or non-linear relationships and the two-way interactions between each of the individual influential parameters with the three sustainability metrics reflected the functions and characteristics within the APEX model and the interrelations among different processes. Strong interactions between the most influential parameters for total biomass, nitrogen loss, and soil carbon change also highlighted the importance of accurately setting these parameters. Identification of influential model parameters for switchgrass sustainability may help guide field measurements and provide further understanding of the interrelated processes in the APEX model. Furthermore, future field experiments can be designed to measure these influential parameters and understand the non-linear relationships identified between influential parameters and response variables. More accurate model parameterization will help improve APEX model performance and our understanding of the possible underlying physiological mechanisms.

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Sensitivity Analysis of the Agricultural Policy/Environmental eXtender (APEX) for Phosphorus Loads in Tile-Drained Landscapes

Cited by 22 publications

References 42 publications

Modified APEX model for Simulating Macropore Phosphorus Contributions to Tile Drains

Modified APEX model for Simulating Macropore Phosphorus Contributions to Tile Drains

Edge‐Of‐Field Evaluation of the Ohio Phosphorus Risk Index

Sensitivity Analysis of the APEX Model for Assessing Sustainability of Switchgrass Grown for Biofuel Production in Central Texas

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